This is one page of the R Handbook for Epidemiologists, but is being printed as a stand-alone page.
You can find the complete handbook on Github
The primary tool to visualize and analyze transmission chains is the package epicontacts, developed by the folks at RECON.
links <- epicontacts::make_epicontacts(linelist = mers_korea_2015$linelist,
contacts = mers_korea_2015$contacts,
directed = TRUE)
# plot without time
plot(links,
selector = FALSE,
height = 700,
width = 700)And in a transmission tree, with date of onset on the x-axis:
Note: this currently requires installing a development version of epicontacts from github… @ttree
summary(links)
##
## /// Overview //
## // number of unique IDs in linelist: 162
## // number of unique IDs in contacts: 97
## // number of unique IDs in both: 97
## // number of contacts: 98
## // contacts with both cases in linelist: 100 %
##
## /// Degrees of the network //
## // in-degree summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 1.0000 0.6049 1.0000 3.0000
##
## // out-degree summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.6049 0.0000 38.0000
##
## // in and out degree summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 1.00 1.21 1.00 39.00
##
## /// Attributes //
## // attributes in linelist:
## age age_class sex place_infect reporting_ctry loc_hosp dt_onset dt_report week_report dt_start_exp dt_end_exp dt_diag outcome dt_death
##
## // attributes in contacts:
## exposure diff_dt_onsetThis tab should stay with the name “Resources”. Links to other online tutorials or resources.